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Journal articles on the topic 'NOISEX database'

Author: Grafiati

Published: 6 September 2023

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1

Zhang, Yan, Zhen-min Tang, Yan-ping Li, and Yang Luo. "A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/723643.

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Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech enhancement block. For the feature selection and voting block, several discriminating features were employed in a voting paradigm for the consideration of reliability and discriminative power. Effectiveness of the proposed approach is compared and evaluated to other VAD techniques by using two well-k

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Qi, Yingmei, Heming Huang, and Huiyun Zhang. "Research on Speech Emotion Recognition Method Based A-CapsNet." Applied Sciences 12, no. 24 (2022): 12983. http://dx.doi.org/10.3390/app122412983.

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Speech emotion recognition is a crucial work direction in speech recognition. To increase the performance of speech emotion detection, researchers have worked relentlessly to improve data augmentation, feature extraction, and pattern formation. To address the concerns of limited speech data resources and model training overfitting, A-CapsNet, a neural network model based on data augmentation methodologies, is proposed in this research. In order to solve the issue of data scarcity and achieve the goal of data augmentation, the noise from the Noisex-92 database is first combined with four differ

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FAROOQ, O., S. DATTA, and M. C. SHROTRIYA. "WAVELET SUB-BAND BASED TEMPORAL FEATURES FOR ROBUST HINDI PHONEME RECOGNITION." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 06 (2010): 847–59. http://dx.doi.org/10.1142/s0219691310003845.

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This paper proposes the use of wavelet transform-based feature extraction technique for Hindi speech recognition application. The new proposed features take into account temporal as well as frequency band energy variations for the task of Hindi phoneme recognition. The recognition performance achieved by the proposed features is compared with the standard MFCC and 24-band admissible wavelet packet-based features using a linear discriminant function based classifier. To evaluate robustness of these features, the NOISEX database is used to add different types of noise into phonemes to achieve si

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Rudramurthy, M. S., V. Kamakshi Prasad, and R. Kumaraswamy. "Speaker Verification Under Degraded Conditions Using Empirical Mode Decomposition Based Voice Activity Detection Algorithm." Journal of Intelligent Systems 23, no. 4 (2014): 359–78. http://dx.doi.org/10.1515/jisys-2013-0085.

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AbstractThe performance of most of the state-of-the-art speaker recognition (SR) systems deteriorates under degraded conditions, owing to mismatch between the training and testing sessions. This study focuses on the front end of the speaker verification (SV) system to reduce the mismatch between training and testing. An adaptive voice activity detection (VAD) algorithm using zero-frequency filter assisted peaking resonator (ZFFPR) was integrated into the front end of the SV system. The performance of this proposed SV system was studied under degraded conditions with 50 selected speakers from t

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Yang, Jie. "Combining Speech Enhancement and Cepstral Mean Normalization for LPC Cepstral Coefficients." Key Engineering Materials 474-476 (April 2011): 349–54. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.349.

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A mismatch between the training and testing in noisy circumstance often causes a drastic decrease in the performance of speech recognition system. The robust feature coefficients might suppress this sensitivity of mismatch during the recognition stage. In this paper, we investigate the noise robustness of LPC Cepstral Coefficients (LPCC) by using speech enhancement with feature post-processing. At front-end, speech enhancement in the wavelet domain is used to remove noise components from noisy signals. This enhanced processing adopts the combination of discrete wavelet transform (DWT), wavelet

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Upadhyaya, Prashant, Omar Farooq, M. R. Abidi, and Priyanka Varshney. "Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition." Archives of Acoustics 40, no. 4 (2015): 609–19. http://dx.doi.org/10.1515/aoa-2015-0061.

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Abstract In building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studied for audio visual automatic speech recognition (AVASR) system under diverse noisy audio conditions. Four sets of visual feature based on Two-Dimensional Discrete Cosine Transform feature (2D-DCT), Principal Component Analysis (PCA), Two-Dimensional Discrete Wavelet Transform followed by DC

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Varga, Andrew, and Herman J. M. Steeneken. "Assessment for automatic speech recognition: II. NOISEX-92: A database and an experiment to study the effect of additive noise on speech recognition systems." Speech Communication 12, no. 3 (1993): 247–51. http://dx.doi.org/10.1016/0167-6393(93)90095-3.

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Yang, Ren Di, and Yan Li Zhang. "Denoising of ECG Signal Based on Empirical Mode Decomposition and Adaptive Noise Cancellation." Applied Mechanics and Materials 40-41 (November 2010): 140–45. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.140.

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To remove the noises in ECG and to overcome the disadvantage of the denoising method only based on empirical mode decomposition (EMD), a combination of EMD and adaptive noise cancellation is introduced in this paper. The noisy ECG signals are firstly decomposed into intrinsic mode functions (IMFs) by EMD. Then the IMFs corresponding to noises are used to reconstruct signal. The reconstructed signal as the reference input of adaptive noise cancellation and the noisy ECG as the basic input, the de-noised ECG signal is obtained after adaptive filtering. The de-noised ECG has high signal-to-noise

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Ataeyan, Mahdieh, and Negin Daneshpour. "Automated Noise Detection in a Database Based on a Combined Method." Statistics, Optimization & Information Computing 9, no. 3 (2021): 665–80. http://dx.doi.org/10.19139/soic-2310-5070-879.

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Data quality has diverse dimensions, from which accuracy is the most important one. Data cleaning is one of the preprocessing steps in data mining which consists of detecting errors and repairing them. Noise is a common type of error, that occur in database. This paper proposes an automated method based on the k-means clustering for noise detection. At first, each attribute (Aj) is temporarily removed from data and the k-means clustering is applied to other attributes. Thereafter, the k-nearest neighbors is used in each cluster. After that a value is predicted for Aj in each record by the near

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Ma, Lilong, Tuanwei Xu, Kai Cao, Yinghao Jiang, Dimin Deng, and Fang Li. "Signal Activity Detection for Fiber Optic Distributed Acoustic Sensing with Adaptive-Calculated Threshold." Sensors 22, no. 4 (2022): 1670. http://dx.doi.org/10.3390/s22041670.

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The key point on analyzing the data stream measured by fiber optic distributed acoustic sensing (DAS) is signal activity detection separating measured signals from environmental noise. The inability to calculate the threshold for signal activity detection accurately and efficiently without affecting the measured signals is a bottleneck problem for current methods. In this article, a novel signal activity detection method with the adaptive-calculated threshold is proposed to solve the problem. With the analysis of the time-varying random noise’s statistical commonality and the short-term energy

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Moreno Escobar, Jesús Jaime, Erika Yolanda Aguilar del Villar, Oswaldo Morales Matamoros, and Liliana Chanona Hernández. "3D22MX: Performance Subjective Evaluation of 3D/Stereoscopic Image Processing and Analysis." Mathematics 11, no. 1 (2022): 171. http://dx.doi.org/10.3390/math11010171.

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This work is divided into three parts: (i) a methodology developed for building a 3D/ stereoscopic database, called 3D22MX, (ii) a software tool designed for degradation of 3D/stereoscopic images, and (iii) a psychophysical experiment carried out for a specific type of noise. The novelty of this work is to integrate these three parts precisely to provide not only professionals who design algorithms to estimate three-dimensional image quality but also those who wish to generate new image databases. For the development of the 3D/stereoscopic database, 15 indoor images and 5 outdoor ones were spa

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Zhang, Yatao, Shoushui Wei, Yutao Long, and Chengyu Liu. "Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality." Journal of Electrical and Computer Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/563915.

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This study explored the performance of multiscale entropy (MSE) for the assessment of mobile ECG signal quality, aiming to provide a reasonable application guideline. Firstly, the MSE for the typical noises, that is, high frequency (HF) noise, low frequency (LF) noise, and power-line (PL) noise, was analyzed. The sensitivity of MSE to the signal to noise ratio (SNR) of the synthetic artificial ECG plus different noises was further investigated. The results showed that the MSE values could reflect content level of various noises contained in the ECG signals. For the synthetic ECG plus LF noise,

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Zhang, Lingwen, Teng Tan, Yafan Gong, and Wenkao Yang. "Fingerprint Database Reconstruction Based on Robust PCA for Indoor Localization." Sensors 19, no. 11 (2019): 2537. http://dx.doi.org/10.3390/s19112537.

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The indoor localization method based on the Received Signal Strength (RSS) fingerprint is widely used for its high positioning accuracy and low cost. However, the propagation behavior of radio signals in an indoor environment is complicated and always leads to the existence of outliers and noises that deviate from a normal RSS value in the database. The fingerprint database containing outliers and noises will severely degrade the performance of an indoor localization system. In this paper, an approach to reconstruct the fingerprint database is proposed with the purpose of mitigating the influe

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Uma, A., and P. Kalpana. "ECG Noise Removal Using Modified Distributed Arithmetic Based Finite Impulse Response Filter." Journal of Medical Imaging and Health Informatics 11, no. 5 (2021): 1444–52. http://dx.doi.org/10.1166/jmihi.2021.3770.

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ECG monitoring is essential to support human life. During signal acquisition, the signals are contaminated by various noises that occur due to different sources. This paper focuses on Baseline wander and Muscle Artifact noise removal using Distributed Arithmetic (DA) based FIR filters. An area-efficient modified DA based FIR filter consists of LUT-less structure and used for noise removal. The performance of the modified DA based FIR filter is compared with the conventional DA FIR filter. An arbitrary real-time ECG record is taken from MIT-BIH database and Baseline Wander noise, Muscle artifac

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Zhang, Peng, Mingfeng Jiang, Yang Li, et al. "An efficient ECG denoising method by fusing ECA-Net and CycleGAN." Mathematical Biosciences and Engineering 20, no. 7 (2023): 13415–33. http://dx.doi.org/10.3934/mbe.2023598.

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<abstract> <p>For wearable electrocardiogram (ECG) acquisition, it was easy to infer motion artifices and other noises. In this paper, a novel end-to-end ECG denoising method was proposed, which was implemented by fusing the Efficient Channel Attention (ECA-Net) and the cycle consistent generative adversarial network (CycleGAN) method. The proposed denoising model was optimized by using the ECA-Net method to highlight the key features and introducing a new loss function to further extract the global and local ECG features. The original ECG signal came from the MIT-BIH Arrhythmia Da

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Hussein, Ahmed F., Warda R. Mohammed, Mustafa Musa Jaber, and Osamah Ibrahim Khalaf. "An Adaptive ECG Noise Removal Process Based on Empirical Mode Decomposition (EMD)." Contrast Media & Molecular Imaging 2022 (August 17, 2022): 1–9. http://dx.doi.org/10.1155/2022/3346055.

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The electrocardiogram (ECG) is a generally used instrument for examining cardiac disorders. For proper interpretation of cardiac illnesses, a noise-free ECG is often preferred. ECG signals, on the other hand, are suffering from numerous noises throughout gathering and programme. This article suggests an empirical mode decomposition-based adaptive ECG noise removal technique (EMD). The benefits of the proposed methods are used to dip noise in ECG signals with the least amount of distortion. For decreasing high-frequency noises, traditional EMD-based approaches either cast off the preliminary fu

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Mohd Apandi, Ziti Fariha, Ryojun Ikeura, Soichiro Hayakawa, and Shigeyoshi Tsutsumi. "An Analysis of the Effects of Noisy Electrocardiogram Signal on Heartbeat Detection Performance." Bioengineering 7, no. 2 (2020): 53. http://dx.doi.org/10.3390/bioengineering7020053.

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Heartbeat detection for ambulatory cardiac monitoring is more challenging as the level of noise and artefacts induced by daily-life activities are considerably higher than monitoring in a hospital setting. It is valuable to understand the relationship between the characteristics of electrocardiogram (ECG) noises and the beat detection performance in the cardiac monitoring system. For this purpose, three well-known algorithms for the beat detection process were re-implemented. The beat detection algorithms were validated using two types of ambulatory datasets, which were the ECG signal from the

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Maas, A., F. Rottensteiner, and C. Heipke. "USING LABEL NOISE ROBUST LOGISTIC REGRESSION FOR AUTOMATED UPDATING OF TOPOGRAPHIC GEOSPATIAL DATABASES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 133–40. http://dx.doi.org/10.5194/isprsannals-iii-7-133-2016.

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Supervised classification of remotely sensed images is a classical method to update topographic geospatial databases. The task requires training data in the form of image data with known class labels, whose generation is time-consuming. To avoid this problem one can use the labels from the outdated database for training. As some of these labels may be wrong due to changes in land cover, one has to use training techniques that can cope with wrong class labels in the training data. In this paper we adapt a label noise tolerant training technique to the problem of database updating. No labelled d

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Maas, A., F. Rottensteiner, and C. Heipke. "USING LABEL NOISE ROBUST LOGISTIC REGRESSION FOR AUTOMATED UPDATING OF TOPOGRAPHIC GEOSPATIAL DATABASES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 133–40. http://dx.doi.org/10.5194/isprs-annals-iii-7-133-2016.

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Supervised classification of remotely sensed images is a classical method to update topographic geospatial databases. The task requires training data in the form of image data with known class labels, whose generation is time-consuming. To avoid this problem one can use the labels from the outdated database for training. As some of these labels may be wrong due to changes in land cover, one has to use training techniques that can cope with wrong class labels in the training data. In this paper we adapt a label noise tolerant training technique to the problem of database updating. No labelled d

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Dwork, Cynthia, Frank McSherry, Kobbi Nissim, and Adam Smith. "Calibrating Noise to Sensitivity in Private Data Analysis." Journal of Privacy and Confidentiality 7, no. 3 (2017): 17–51. http://dx.doi.org/10.29012/jpc.v7i3.405.

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We continue a line of research initiated in Dinur and Nissim (2003); Dwork and Nissim (2004); and Blum et al. (2005) on privacy-preserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function $f$ mapping databases to reals, the so-called {\em true answer} is the result of applying $f$ to the database. To protect privacy, the true answer is perturbed by the addition of random noise generated according to a carefully chosen distribution, and this response, the true answer plus noise, is returned to the user. Previous

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Kang, Yimei, and Wang Pan. "A Novel Approach of Low-Light Image Denoising for Face Recognition." Advances in Mechanical Engineering 6 (January 1, 2014): 256790. http://dx.doi.org/10.1155/2014/256790.

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Illumination variation makes automatic face recognition a challenging task, especially in low light environments. A very simple and efficient novel low-light image denoising of low frequency noise (DeLFN) is proposed. The noise frequency distribution of low-light images is presented based on massive experimental results. The low and very low frequency noise are dominant in low light conditions. DeLFN is a three-level image denoising method. The first level denoises mixed noises by histogram equalization (HE) to improve overall contrast. The second level denoises low frequency noise by logarith

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Jain, Anshika, and Maya Ingle. "PERFORMANCE ANALYSIS OF NOISE REMOVAL TECHNIQUES FOR FACIAL IMAGES- A COMPARATIVE STUDY." BSSS journal of computer 12, no. 1 (2021): 1–10. http://dx.doi.org/10.51767/jc1201.

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Image de-noising has been a challenging issue in the field of digital image processing. It involves the manipulation of image data to produce a visually high quality image. While maintaining the desired information in the quality of an image, elimination of noise is an essential task. Various domain applications such as medical science, forensic science, text extraction, optical character recognition, face recognition, face detection etc. deal with noise removal techniques. There exist a variety of noises that may corrupt the images in different ways. Here, we explore filtering techniques viz.

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Alia Zainudin, Noraina, Ain Nazari, Mohd Marzuki Mustafa, Wan NurShazwani Wan Zakaria, Nor Surayahani Suriani, and Wan Nur Hafsha Wan Kairuddin. "Glaucoma detection of retinal images based on boundary segmentation." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 377. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp377-384.

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<p>The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. The

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Su, Pei-Chun, Elsayed Z. Soliman, and Hau-Tieng Wu. "Robust T-End Detection via T-End Signal Quality Index and Optimal Shrinkage." Sensors 20, no. 24 (2020): 7052. http://dx.doi.org/10.3390/s20247052.

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An automatic accurate T-wave end (T-end) annotation for the electrocardiogram (ECG) has several important clinical applications. While there have been several algorithms proposed, their performance is usually deteriorated when the signal is noisy. Therefore, we need new techniques to support the noise robustness in T-end detection. We propose a new algorithm based on the signal quality index (SQI) for T-end, coined as tSQI, and the optimal shrinkage (OS). For segments with low tSQI, the OS is applied to enhance the signal-to-noise ratio (SNR). We validated the proposed method using eleven shor

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Amara korba, Mohamed Cherif, Houcine Bourouba, and Rafik Djemili. "FEATURE EXTRACTION ALGORITHM USING NEW CEPSTRAL TECHNIQUES FOR ROBUST SPEECH RECOGNITION." Malaysian Journal of Computer Science 33, no. 2 (2020): 90–101. http://dx.doi.org/10.22452/mjcs.vol33no2.1.

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In this work, we propose a novel feature extraction algorithm that improves the robustness of automatic speech recognition (ASR) systems in the presence of various types of noise. The proposed algorithm uses a new cepstral technique based on the differential power spectrum (DPS) instead of the power spectrum (PS), the algorithm replaces the logarithmic non linearity by the power function. In order to reduce cepstral coefficients mismatches between training and testing conditions, we used the mean and variance normalization, then we apply auto-regression movingaverage filtering (MVA) in the cep

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Thiemann, Joachim, Nobutaka Ito, and Emmanuel Vincent. "The diverse environments multi-channel acoustic noise database: A database of multichannel environmental noise recordings." Journal of the Acoustical Society of America 133, no. 5 (2013): 3591. http://dx.doi.org/10.1121/1.4806631.

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Sun, Zhe, Zheng-Ping Hu, Meng Wang, Fan Bai, and Bo Sun. "Robust Facial Expression Recognition with Low-Rank Sparse Error Dictionary Based Probabilistic Collaborative Representation Classification." International Journal on Artificial Intelligence Tools 26, no. 04 (2017): 1750017. http://dx.doi.org/10.1142/s0218213017500178.

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The performance of facial expression recognition (FER) would be degraded due to some factors such as individual differences, Gaussian random noise and so on. Prior feature extraction methods like Local Binary Patterns (LBP) and Gabor filters require explicit expression components, which are always unavailable and difficult to obtain. To make the facial expression recognition (FER) more robust, we propose a novel FER approach based on low-rank sparse error dictionary (LRSE) to remit the side-effect caused by the problems above. Then the query samples can be represented and classified by a proba

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Robert, J., and B. P. Pathak. "Noise Levels: A database of industrial noise level measurements." Online Review 12, no. 4 (1988): 211–17. http://dx.doi.org/10.1108/eb024280.

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BENOSMAN, M. M., F. BEREKSI-REGUIG, and E. GORAN SALERUD. "STRONG REAL-TIME QRS COMPLEX DETECTION." Journal of Mechanics in Medicine and Biology 17, no. 08 (2017): 1750111. http://dx.doi.org/10.1142/s0219519417501111.

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Heart rate variability (HRV) analysis is used as a marker of autonomic nervous system activity which may be related to mental and/or physical activity. HRV features can be extracted by detecting QRS complexes from an electrocardiogram (ECG) signal. The difficulties in QRS complex detection are due to the artifacts and noises that may appear in the ECG signal when subjects are performing their daily life activities such as exercise, posture changes, climbing stairs, walking, running, etc. This study describes a strong computation method for real-time QRS complex detection. The detection is impr

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Moore, Brian C. J., Larry E. Humes, Graham Cox, David Lowe, and Hedwig E. Gockel. "Modification of a Method for Diagnosing Noise-Induced Hearing Loss Sustained During Military Service." Trends in Hearing 26 (January 2022): 233121652211450. http://dx.doi.org/10.1177/23312165221145005.

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Moore (2020) proposed a method for diagnosing noise-induced hearing loss (NIHL) sustained during military service, based on an analysis of the shapes of the audiograms of military personnel. The method, denoted M-NIHL, was estimated to have high sensitivity but low-to-moderate specificity. Here, a revised version of the method, denoted rM-NIHL, was developed that gave a better balance between sensitivity and specificity. A database of 285 audiograms of military noise-exposed men was created by merging two previously used databases with a new database, randomly shuffling, and then splitting int

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Kirmizitas, Hikmet, and Nurettin Besli. "Image and Texture Independent Deep Learning Noise Estimation Using Multiple Frames." Elektronika ir Elektrotechnika 28, no. 6 (2022): 42–47. http://dx.doi.org/10.5755/j02.eie.30586.

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In this study, a novel multiple frame based image and texture independent Convolutional Neural Network (CNN) noise estimator is introduced. Noise estimation is a crucial step for denoising algorithms, especially for ones that are called “non-blind”. The estimator works for additive Gaussian noise for varying noise levels. The noise levels studied in this work have a standard deviation equal to 5 to 25 increasing 5 by 5. Since there is no database for noisy multiple images to train and validate the network, two frames of synthetic noisy images with a variety of noise levels are created by addin

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Santos-Domínguez, David, Soledad Torres-Guijarro, Antonio Cardenal-López, and Antonio Pena-Gimenez. "ShipsEar: An underwater vessel noise database." Applied Acoustics 113 (December 2016): 64–69. http://dx.doi.org/10.1016/j.apacoust.2016.06.008.

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He, Jian Ping, and Ning Wang. "The Research on the Recognition Technique of Rock AE and Noise Signal." Advanced Materials Research 168-170 (December 2010): 293–97. http://dx.doi.org/10.4028/www.scientific.net/amr.168-170.293.

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AE signal waveform Envelope is damped oscillation process, its maximum amplitude descending edge Envelope is exponential rule decay oscillation process ，others noises higher than oscillation delay. The thesis analysis rock AE and noise signal in the mine，on the basis of Fourier transform spectral analysis to found the noise spectrum characteristics, setting up noise database, according to the site data acquisition rock AE and environmental noise signal, with its characters spectral data to wavelet multi-scale decomposed，supplemented by Fourier transform spectral analysis, basing on noise spect

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Lin, Haicai, Ruixia Liu, and Zhaoyang Liu. "ECG Signal Denoising Method Based on Disentangled Autoencoder." Electronics 12, no. 7 (2023): 1606. http://dx.doi.org/10.3390/electronics12071606.

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The electrocardiogram (ECG) is widely used in medicine because it can provide basic information about different types of heart disease. However, ECG data are usually disturbed by various types of noise, which can lead to errors in diagnosis by doctors. To address this problem, this study proposes a method for denoising ECG based on disentangled autoencoders. A disentangled autoencoder is an improved autoencoder suitable for denoising ECG data. In our proposed method, we use a disentangled autoencoder model based on a fully convolutional neural network to effectively separate the clean ECG data

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Kish, Laszlo B., and Walter C. Daugherity. "Entanglement, and Unsorted Database Search in Noise-Based Logic." Applied Sciences 9, no. 15 (2019): 3029. http://dx.doi.org/10.3390/app9153029.

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We explore the collapse of “wavefunction” and the measurement of entanglement in the superpositions of hyperspace vectors in classical physical instantaneous-noise-based logic (INBL). We find both similarities with and major differences from the related properties of quantum systems. Two search algorithms utilizing the observed features are introduced. For the first one we assume an unsorted names database set up by Alice that is a superposition (unknown by Bob) of up to n = 2N strings; those we call names. Bob has access to the superposition wave and to the 2N reference noises of the INBL sys

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Zhou, Jiena, Zhihao Shi, Lifang Zhou, Yong Hu, and Meibian Zhang. "Occupational noise-induced hearing loss in China: a systematic review and meta-analysis." BMJ Open 10, no. 9 (2020): e039576. http://dx.doi.org/10.1136/bmjopen-2020-039576.

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ObjectiveMost of the Chinese occupational population are becoming at risk of noise-induced hearing loss (NIHL). However, there is a limited number of literature reviews on occupational NIHL in China. This study aimed to analyse the prevalence and characteristics of occupational NIHL in the Chinese population using data from relevant studies.DesignSystematic review and meta-analysis.MethodsFrom December 2019 to February 2020, we searched the literature through databases, including Web of Science, PubMed, MEDLINE, Scopus, the China National Knowledge Internet, Chinese Sci-Tech Journal Database (

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Hamza, Nisreen Ryadh, Rasha Ail Dihin, and Mohammed Hasan Abdulameer. "A hybrid image similarity measure based on a new combination of different similarity techniques." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1814. http://dx.doi.org/10.11591/ijece.v10i2.pp1814-1822.

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Image similarity is the degree of how two images are similar or dissimilar. It computes the similarity degree between the intensity patterns in images. A new image similarity measure named (HFEMM) is proposed in this paper. The HFEMM is composed of two phases. Phase 1, a modified histogram similarity measure (HSSIM) is merged with feature similarity measure (FSIM) to get a new measure called (HFM). In phase 2, the resulted (HFM) is merged with error measure (EMM) in order to get a new similarity measure, which is named (HFEMM). Different kindes of noises for example Gaussian, Uniform, and salt

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Garg, Meenu, and Amandeep Verma. "An Enhanced LSDBIQ Algorithm for Full Reference Image Quality Assessment for Multi Distorted Images." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 8 (2017): 41. http://dx.doi.org/10.23956/ijarcsse.v7i8.18.

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Image processing is an emerging technology as image is used in various fields like medical and education. Images may corrupt due to the various categories of noises. Image quality reduces because of the image acquisition or transmission. Noise reduction is the main focus to retain the quality of the image. For the removal of this noise, there are various techniques and filters. Before applying further processing on the image, noise should be removed from the image. In this paper we deal with with a practical and effectual IQA model, called LSDBIQ (local standard deviation based image quality).

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Jaenul, Ariep, Shahad Alyousif, Ali Amer Ahmed Alrawi, and Samer K. Salih. "Robust Approach of De-noising ECG Signal Using Multi-Resolution Wavelet Transform." International Journal of Engineering & Technology 7, no. 4.11 (2018): 5. http://dx.doi.org/10.14419/ijet.v7i4.11.20678.

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The ECG signal expresses the behavior of human heart against time. The analysis of this signal performs great information for diagnosing different cardiac diseases. In other hand, the ECG signal used for analyzing must be clean from any type of noises that corrupted it by the external environment. In this paper, a new approach of ECG signal noise reduction is proposed to minimize noise from all parts of ECG signal and maintains main characteristics of ECG signal with lowest changes. The new approach applies simple scaling down operation on the detail resolution in the wavelet transform space o

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Dai, Peishan, Hanwei Sheng, Jianmei Zhang, Ling Li, Jing Wu, and Min Fan. "Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing." International Journal of Biomedical Imaging 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/5075612.

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Retinal fundus image plays an important role in the diagnosis of retinal related diseases. The detailed information of the retinal fundus image such as small vessels, microaneurysms, and exudates may be in low contrast, and retinal image enhancement usually gives help to analyze diseases related to retinal fundus image. Current image enhancement methods may lead to artificial boundaries, abrupt changes in color levels, and the loss of image detail. In order to avoid these side effects, a new retinal fundus image enhancement method is proposed. First, the original retinal fundus image was proce

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Dance, Stephen, and Lindsay McIntyre. "The Quiet Project – UK Acoustic Community’s response to COVID19 during the easing of lockdown." Noise Mapping 8, no. 1 (2021): 32–40. http://dx.doi.org/10.1515/noise-2021-0003.

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Abstract The COVID-19 lockdown created a new kind of environment both in the UK and globally, never experienced before or likely to occur again. A vital and time-critical working group was formed with the aim of gathering crowd-source high quality baseline noise levels and other supporting information across the UK during the lock-down and subsequent periods. The acoustic community were mobilised through existing networks engaging private companies, public organisations and academics to gather data in accessible places. In addition, pre-existing on-going measurements from major infrastructure

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Thangarajan, Ahilandeswari, and Vivekanandan Kalimuthu. "CBIR with Partial Input of Unshaped Images Using Compressed-Pixel Matching Algorithm." International Journal of Engineering & Technology 7, no. 3.27 (2018): 206. http://dx.doi.org/10.14419/ijet.v7i3.27.17762.

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Many works have been done to find out whether given image is in the database using Content Based Image Retrieval (CBIR) techniques. However if the query image is unshaped or noise filled then retrieval of that image in the database is difficult .We propose an approach by which for any shape of input image the databases is searched and the most relevant image is retrieved. Results provides better accuracy than existing one and time elapsed also reduced because of making comparison after compression of both partial image and images from the database. The attainment of the proposed system is asse

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Bagherzadeh Cham, Masumeh, Mohammad Ali Mohseni-Bandpei, Mahmood Bahramizadeh, Saeed Kalbasi, and Akbar Biglarian. "The clinical and biomechanical effects of subthreshold random noise on the plantar surface of the foot in diabetic patients and elder people: A systematic review." Prosthetics and Orthotics International 40, no. 6 (2016): 658–67. http://dx.doi.org/10.1177/0309364616631351.

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Background:Central nervous system receives information from foot mechanoreceptors in order to control balance and perform movement tasks. Subthreshold random noise seems to improve sensitivity of the cutaneous mechanoreceptor.Objectives:The purpose of this study was to systematically review published evidence conducted to evaluate the clinical and biomechanical effects of subthreshold random noise on the plantar surface of the foot in diabetic patients and elder people.Study design:Systematic review.Methods:A literature search was performed in PubMed, Scopus, ScienceDirect, Web of Knowledge, C

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Li, Lanting, Tianliang Lu, Xingbang Ma, Mengjiao Yuan, and Da Wan. "Voice Deepfake Detection Using the Self-Supervised Pre-Training Model HuBERT." Applied Sciences 13, no. 14 (2023): 8488. http://dx.doi.org/10.3390/app13148488.

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In recent years, voice deepfake technology has developed rapidly, but current detection methods have the problems of insufficient detection generalization and insufficient feature extraction for unknown attacks. This paper presents a forged speech detection method (HuRawNet2_modified) based on a self-supervised pre-trained model (HuBERT) to improve detection (and address the above problems). A combination of impulsive signal-dependent additive noise and additive white Gaussian noise was adopted for data boosting and augmentation, and the HuBERT model was fine-tuned on different language databa

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Dalal, Virupaxi, and Satish Bhairannawar. "Efficient de-noising technique for electroencephalogram signal processing." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (2022): 603. http://dx.doi.org/10.11591/ijai.v11.i2.pp603-612.

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An electroencephalogram (EEG) is a recording of various frequencies of electrical activity in the brain. EEG signal is very useful for diagnosis of various brain related diseases at early stage to prevent severe issues which may lead to loss of life. The raw EEG signal captured through the leads contain different type of noises which is not susceptible for diagnosis. In this paper, an efficient algorithm is proposed to process the raw EEG signal to combat the noise. To obtain noiseless EEG data, the likelihood test ratio is applied to interference computation block. The likelihood ratio test c

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Santos, Mónica, Armando Almeida, Catarina Lopes, and Tiago Oliveira. "Ruído: Medidas de Proteção Coletivas e Individuais." Revista Portuguesa de Saúde Ocupacional 9 (June 30, 2020): S82—S90. http://dx.doi.org/10.31252/rpso.18.04.2020.

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Introduction / framework / objectives Noise is an occupational risk factor extensively addressed in the Occupational Health literature. However, its pathophysiological consequences have traditionally been emphasized, sometimes neglecting more detailed explanations concerning personal protective equipment and collective protective measures. Methodology This is a Scoping Review, initiated by a September 2019 search of the databases “CINALH plus with full text, Medline with full text, Cochrane Database of Abstracts of Reviews of Effects, Cochrane Central Register of Controlled Trials, Cochrane Da

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Li, Qiuying, Tao Zhang, Yanzhang Geng, and Zhen Gao. "Microphone array speech enhancement based on optimized IMCRA." Noise Control Engineering Journal 69, no. 6 (2021): 468–76. http://dx.doi.org/10.3397/1/376944.

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Microphone array speech enhancement algorithm uses temporal and spatial informa- tion to improve the performance of speech noise reduction significantly. By combining noise estimation algorithm with microphone array speech enhancement, the accuracy of noise estimation is improved, and the computation is reduced. In traditional noise es- timation algorithms, the noise power spectrum is not updated in the presence of speech, which leads to the delay and deviation of noise spectrum estimation. An optimized im- proved minimum controlled recursion average speech enhancement algorithm, based on a mi

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Picaut, Judicaël, Ayoub Boumchich, Erwan Bocher, Nicolas Fortin, Gwendall Petit, and Pierre Aumond. "A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment." International Journal of Environmental Research and Public Health 18, no. 15 (2021): 7777. http://dx.doi.org/10.3390/ijerph18157777.

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Noise is a major source of pollution with a strong impact on health. Noise assessment is therefore a very important issue to reduce its impact on humans. To overcome the limitations of the classical method of noise assessment (such as simulation tools or noise observatories), alternative approaches have been developed, among which is collaborative noise measurement via a smartphone. Following this approach, the NoiseCapture application was proposed, in an open science framework, providing free access to a considerable amount of information and offering interesting perspectives of spatial and t

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Gendron, Marlin L., and Juliette W. Ioup. "Wavelet Multi-scale Edge Detection for Extraction of Geographic Features to Improve Vector Map Databases." Journal of Navigation 53, no. 1 (2000): 79–92. http://dx.doi.org/10.1017/s0373463399008607.

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Although numerous at smaller geographic scales, vector databases often do not exist at the more detailed, larger scales. A possible solution is the use of image processing techniques to detect edges in high-resolution satellite imagery. Features such as roads and airports are formed from the edges and matched up with similar features in existing low-resolution vector map databases. By replacing the old features with the new more accurate features, the resolution of the existing map database is improved. To accomplish this, a robust edge detection algorithm is needed that will perform well in n

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Kostoulas, Theodoros, Thomas Winkler, Todor Ganchev, Nikos Fakotakis, and Joachim Köhler. "The MoveOn database: motorcycle environment speech and noise database for command and control applications." Language Resources and Evaluation 47, no. 2 (2013): 539–63. http://dx.doi.org/10.1007/s10579-013-9222-7.

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